Artificial Intelligence In Medicine: Deep Learning

This course builds on fundamental machine learning algorithms such as Support Vector Machines, Random Forests, and Logistic Regression, which were introduced in our previous modules as well as the technical course on Python. We now delve deeper into neural networks, exploring their critical role in AI in medicine and how they can be used to analyze medical images for instance. This course will guide you through the basic structure of neural networks, and the various steps needed to build a convolutional neural network. We will also cover more advanced topics like the challenges of training deep networks, the importance of matrices and tensors, and how these mathematical constructs form the building blocks of deep learning algorithms. Join us as we navigate the intricacies of AI in medicine and unlock the potential of these powerful models.

Learn more about the Quality and Patient Safety initiative

1. Understand the fundamental concepts of neural networks, including their structure, types, and training methods.
2. Develop a strong foundation in linear algebra, including matrices and tensors, and their applications in deep learning algorithms.
3. Learn the key components and operations of convolutional neural networks (CNNs), including convolutional filters, pooling layers, and fully connected layers.
4. Master the skills to design, train, and optimize CNN models, including hyperparameter tuning and techniques to prevent overfitting.

The University of Florida College of Medicine is accredited by the Accreditation Council for Continuing Medical Education (ACCME) to provide continuing medical education for physicians.

Credit Designation

The University of Florida College of Medicine designates this Enduring Material for a maximum of 12.00 AMA PRA Category 1 Credits™. Physicians should claim only the credit commensurate with the extent of their participation in the activity.

For CME general questions, please contact
Email: [email protected]

Mitigation of Relevant Financial Relationships

University of Florida College of Medicine adheres to the ACCME’s Standards for Integrity and Independence in Accredited Continuing Education. All individuals in a position to control a CME activity's content, including faculty, planners, reviewers, and/or others, must disclose all financial relationships with ineligible companies (commercial interests). Conflict of interest information for the CME Advisory Committee members can be found on the following website: https://cme.ufl.edu/disclosure. All relevant financial relationships have been mitigated.

Member Information

Role in activity

Nature of Relationship(s) / Name of Ineligible Company(s)

Chris Giordano, MD
Clinical Professor
University of Florida

Faculty

Nothing to disclose

Francois Modave, PhD

Faculty

Consulting Fee-Genzyme Corporation (Relationship has ended)

Patrick Tighe, MD
Associate Dean for AI Applications
University of Florida

Faculty

Stocks or stock options, excluding diversified mutual funds-3M Health Care|Stocks or stock options, excluding diversified mutual funds-Microsoft|Stocks or stock options, excluding diversified mutual funds-GE Healthcare|Stocks or stock options, excluding diversified mutual funds-Solventum|Stocks or stock options, excluding diversified mutual funds-Apple